Periodic Reporting for period 4 - MemoryDynamics (Writing and editing of memories from acquisition to long-term consolidation)
Okres sprawozdawczy: 2021-04-01 do 2021-09-30
Nervous systems produce adaptive behaviour, arguably their most important function, through learning and memory. Memories ensure that what is learned will be available for later retrieval. Upon the initial learning process, synaptic plasticity important for memory consolidation is triggered within minutes, but whether, and in which form memories will be retained more permanently can be influenced by information and insights gained after the initial trigger. This research program addresses the functional roles of learning-related plasticity processes unfolding subsequent to acquisition in learning and memory. We investigate how hippocampal memories are shaped during several hours after acquisition through network activity and addition of new information through experience, and how these processes involve dedicated neuronal circuits and systems. Furthermore, we study how shaped memories are then long-term consolidated for future use, and how memories are further modified through subsequent learning. This research produces fundamental insights into how learning leads to adaptive behaviour through writing and editing of memories.
We have made progress in understanding the role of parvalbumin (PV) interneuron plasticity in the consolidation of memories. We found that learning-induced plasticity of local PV basket cells is specifically required for long-term memory consolidation, presumably to support off-line network activity. Upon induction, PV neuron plasticity depended on local D1/5 dopamine receptor signaling during the first 5h to regulate its magnitude, and at 12-14h after initial acquisition for its sustainment, ensuring memory consolidation. Our results reveal general network mechanisms of long-term memory consolidation requiring plasticity of PV basket cells induced upon acquisition and sustained subsequently through D1/5 receptor signaling (Karunakaran et al., Nature Neurosci. 2016). In a study addressing network mechanisms of memory consolidation, we investigated whether repeated experiences might be integrated individually as they occur, or whether they might be combined within dedicated time windows, possibly promoting quality control. We discovered that learning processes consist of dedicated 5h time units, involving maintenance of specific system-wide neuronal assemblies through network activity and expression of the immediate early gene cFos (Chowdhury and Caroni, Nature Commun., 2018). We further addressed systems mechanisms of memory consolidation and modification in flexible learning. We focused on the specific contributions of two prefrontal cortical areas, prelimbic (PreL) and infralimbic (IL) cortex. We found that PreL is required during new learning to apply previously learned associations, whereas activity in IL is required to learn associations alternative to the previous ones. Notably, the role of IL for alternative learning was established 12-14h after the initial learning process, that is off-line, presumably through processes of systems consolidation. Our results define specific and opposing roles of PreL and IL to together flexibly support new learning and provide circuit evidence that IL-mediated learning of alternative associations depends on direct reciprocal PreL<->IL connectivity (Mukherjee and Caroni, Nature Commun., 2018). Last but not least, we investigated whether the circuit mechanisms of memory consolidation and plasticity might be affected in a genetic mouse model of schizophrenia. We discovered that they not only are dramatically and specifically affected in a network that had been implicated in mental health by previous studies, but that their pharmacological rescue within that same network during a critical period late in adolescence is sufficient to produce a long-lasting rescue of cognition in this model of high-penetrance schizophrenia. These results suggest that a severe mental health condition such as schizophrenia might be treatable upon targeting of specific network deficits during a critical period late in adolescence, when patients exhibit first episode of their condition (Mukherjee et al., Cell, 2019).
In summary, our specific approach focusing on circuit and network mechanisms of memory-related plasticity has yielded novel insights into network mechanisms of flexible learning in the brain. In parallel, the same approach led to novel insights into network mechanisms leading to schizophrenia, uncovering a potential approach for long-lasting treatment of this severe and chronic condition. These findings were disseminated through publications addressing broad audiences of scientists, as well as through international Conferences and releases to the press.
In summary, our specific approach focusing on circuit and network mechanisms of memory-related plasticity has yielded novel insights into network mechanisms of flexible learning in the brain. In parallel, the same approach led to novel insights into network mechanisms leading to schizophrenia, uncovering a potential approach for long-lasting treatment of this severe and chronic condition. These findings were disseminated through publications addressing broad audiences of scientists, as well as through international Conferences and releases to the press.
We have made inroads in understanding processes of memory consolidation and modification linked to specific neuronal assemblies, their modulation through dopamine signaling, and how specific interactions between dedicated brain areas bring about adaptive flexible learning. In addition to defining the role of subpopulations of neurons within neuronal assemblies for learning and memory, we made fundamental progress in elucidating how specific networks of brain areas and their associated neuronal assemblies bring about flexible learning. These cellular and systems studies provide insights into how brain areas work together to produce flexible adaptive behavior, thereby advancing our understanding of the functional organization of cognition in the brain. This research also has broad implications for how the brain is affected in psychiatric and neurodegenerative diseases. Indeed, we could exploit the new network knowledge to uncover a mechanism and potential treatment for schizophrenia.